Jindra Fremuth (Prague, 2006-09) calls his 17 years as CEO at O2 Czech Republiic “a blast,” and he’s every bit as excited about what comes next, leading AI transformation at PPF Group. He spoke with us about leaving telco to learn new businesses, building AI cultures from the top down and the bottom up, and the family of AI agents that helps him run everything from his work to his household.
After 17 years at O2, and nearly a decade leading it in the Czech Republic, what are you most proud of?
First of all, I had a blast. What I'm proud of most is consistency. We moved into continuous growth in mobile revenues around 2013, fixed revenues started growing in 2016, and we never stopped. Over the past nine years, EBITDA has grown by more than 50%. We never had a negative year. In terms of P&L performance, I'm really proud of what we did, and O2 is in the best shape I can remember.
We also built O2 into a technology-leading brand. That was always my objective, not only for customers, but for employees. It helped us attract technology enthusiasts and very fact-based people. And I'm proud of the team and the culture we built: strong management, a non-corporate spirit, and really interesting AI capabilities.
What is your mission as PPF’s new Chief AI Transformation Officer? Do you already have a strategic one-pager?
I have a one-pager, as well as many more pages. I look at the role in two dimensions: operational and strategic.
Operationally, my job is to help transform existing PPF businesses with AI: understand the opportunities and risks, define the strategy and priorities, and build the operating model behind it. I think about that operating model in four areas: governance and organization; data and data platforms; HW and SW technology; and people, culture and education.
Strategically, I see myself as an advisor to the shareholders. PPF is a portfolio of assets, so you're constantly asking where to invest, where to divest and where to change direction. My role is to understand how AI changes those decisions, because I believe it can change them significantly.
Across such a broad portfolio, what do you expect will be the hardest part?
Prioritization. I know telco in very deep detail, but I still need to learn the other businesses. And the asset base is complex: multiple industries, companies and regions, each with many AI opportunities and risks.
The core mission, especially at the beginning, is to decide what we should go after based on facts, value, impact and feasibility, and what we should deprioritize to make room for something better. If this were one company in one industry, it would be much easier.
What are you most excited to learn or explore in the new role?
It gives me the opportunity to step out of telco, where I've been for ages, and learn new businesses. That's one of the reasons I wanted to do this.
I honestly don't remember the last time I was so excited about my work. Last year I turned 50, so finding this kind of motivation is not automatic. But the deeper I go into the AI rabbit hole, the more I like it and the more enthusiastic I get.
How do you approach the human side of AI transformation?
This topic alone could be a two-hour meeting. At O2, we learned that you need both top-down and bottom-up change. One is not enough.
Top-down, leadership has to be the role model: set clear priorities and create the environment. More than two years ago, we appointed in O2 about 40 AI ambassadors across the company. We also gave employees tools to experiment with: our own chatbots, a secure AI sandbox, continuously updated set of LLMs and other tools.
Bottom-up is just as important. Individuals and small teams need to come up with ideas, test them in their own area and then scale what works. At our first AI awards, we already had around 30 projects competing, from large investments to a single analyst building a tool for their own work. That showed people that you don't need a huge team or budget to benefit from AI.
There’s a common assumption that AI favors younger, more technical people. Do you agree?
I actually believe the opposite. AI lets people who had to be extremely deep and narrow become more general, because the tools can do more of the deep, narrow work for them in areas they do not master.
So I would argue you need less technical skill than before. What you need are people who understand the context, know how value is created and can ask the right questions. And most of all people who are naturally curious.
If you have a very capable AI problem-solving agent, who is better positioned to create value: a young technical person with no experience of the business, industry or customers, or a less technical person who knows the customers and understands how the business creates value? I would argue it's the second group. People who think the future belongs only to young tech-savvy people may have it exactly backwards. But in general, we are talking about the democratization of intelligence, which is something all can benefit from.
How do you think AI will change the consulting profession?
Consulting is harder than it used to be; definitely harder than in my time. Clients are more sophisticated, and now they also have tools that can partially replace some consulting work. Consultants need to find a redesigned value proposition and new sources of value.
At the same time, AI creates a huge opportunity. Every company is asking the same question: how do I transform in the age of AI while everyone else is transforming too? Consultants can help answer that.
What from your McKinsey years do you still carry with you today?
A lot. It was an incredible experience, very positive overall. I still use the problem-solving approaches and frameworks: how to break something really complex into smaller chunks and how to prioritize based on value. That's extremely important for me.
I also learned a lot of soft skills. Working with clients is challenging, and that's where you learn the most. I had plenty of opportunities to be outside my comfort zone.
You spend a lot of time experimenting with AI. What’s your go-to tool?
I have many, but I've basically built my own little agent community. I have a grandmaster agent of agents, and a family of agents that serve it. I only speak to the grandmaster and keep developing the community.
I find it fascinating for two reasons. First, I learn a huge amount. Second, if you want to be in my type of position, you need hands-on experience – the more hands-on, the better. It makes abstract concepts concrete and much easier to explain. And it's infectious: you can really light a fire in other people by showing them what AI can do in your own day-to-day work.
What’s the boldest thing you’ve tried with AI, and what would you never delegate?
I don't really know what counts as the boldest move, because nowadays I use AI for almost everything. It helps me at work and in my private life: running the household, planning trips, making purchasing decisions, managing finances.
As for what I would never delegate: I never say never. I'm ready to try almost anything. When it comes to AI, I think it's dangerous to use the word 'never.'
You’re clearly an AI optimist. How do you think about the risks connected with AI?
The risks are immense, and guardrails and human controls are extremely important. I spend a lot of time thinking about that.
But I also try to be practical. AI is here. It's not going anywhere. We need to deal with reality.
